Purpose: This study aimed to assess phenotypic variation in the coronal plane of knees with anteromedial osteoarthritis using the functional knee phenotype classification, before and after treatment with medial unicompartmental knee arthroplasty (UKA).
Methods: The study comprised 1000 knees of 835 patients (45% females, 55% males, 90% Caucasian) who underwent medial UKA for anteromedial osteoarthritis. Pre and postoperative alignment was evaluated through the hip-knee-ankle angle (HKA), femoral mechanical angle (FMA), and tibial mechanical angle (TMA). Knees were classified according to the functional knee phenotype system which combines limb phenotype (HKA), and femoral and tibial knee phenotypes (FMA and TMA, respectively). Restoration of prearthritic coronal alignment following medial UKA was evaluated by phenotype.
Results: Preoperatively, 76 distinct and 25 relevant (prevalence ≥1%) functional knee phenotypes were identified, of which VAR 6°VAR 3°NEU 0° was the most common (9.4% of knees). The most prevalent limb phenotype, VAR 6°, comprised 15 distinct knee phenotypes (FMA and TMA combinations). Postoperatively, 58 distinct and 17 relevant functional knee phenotypes were observed, of which VAR 3°NEU 0°NEU 0° had the highest prevalence at 18.3%. Knees with combined tibial and femoral deformities were associated with a lower probability of restoration of prearthritic coronal alignment following medial UKA, compared to knees without extra-articular deformity, or knees with an isolated tibial or femoral deformity.
Conclusion: Phenotype analysis using the functional knee phenotype system demonstrated a wide diversity of coronal alignment phenotypes among knees with anteromedial osteoarthritis in a predominantly Caucasian population. Following medial UKA, a reduction from 25 preoperative to 17 postoperative relevant phenotypes was observed. Consideration of phenotypic variation can be of importance when aiming to restore prearthritic coronal alignment during medial UKA.
Level Of Evidence: Level III, retrospective cohort study.
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http://dx.doi.org/10.1002/ksa.12043 | DOI Listing |
Phys Ther
January 2025
IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy.
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Aging Clin Exp Res
January 2025
Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, 710054, China.
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Texas Children's Hospital, Houston, Texas, USA.
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Neuro-robotics Laboratory, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan.
Reliable proprioception and feedback from soft sensors are crucial for enabling soft robots to function intelligently in real-world environments. Nevertheless, soft sensors are fragile and are susceptible to various damage sources in such environments. Some researchers have utilized redundant configuration, where healthy sensors compensate instantaneously for lost ones to maintain proprioception accuracy.
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January 2025
Department of Physical Therapy, Louisiana State University Health Sciences Center- New Orleans, New Orleans, LA, United States.
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